Advanced R-course 2025
Bioinformatics Core Facility CECAD
2025-11-21
git clone https://github.com/CECADBioinformaticsCoreFacility/Advanced_R_course_2025.git
https://cecadbioinformaticscorefacility.github.io/Advanced_R_course_2025/
Session 1 :: Introduction
flowchart TD A[[Hypothesis & Experiment Design]] --> B[[RNA preparation]] B --> C[[Library Generation]] C --> D[[Sequencing]] D --> E[[QC of Raw Data]] E --> F[[Read Alignment]] F --> G[[Quantification]] G --> H[[Differential Expression Analysis]] H --> I[[Functional Profiling]]
flowchart TD A[[Hypothesis & Experiment Design]] --> B[[RNA preparation]] B --> C[[Library Generation]] C --> D[[Sequencing]] D --> E[[QC of Raw Data]] E --> F[[Read Alignment]] F --> G[[Quantification]] G --> H[[Differential Expression Analysis]] H --> I[[Functional Profiling]] style A fill:#228B22,stroke:#333,stroke-width:2px,color:#ffffff,font-weight:bold
What scientific questions or applications am I interested in?
What experimental design will best address my questions?
Important
Always consult with a bioinformatician during the experimental design phase!
flowchart TD A[[Hypothesis & Experiment Design]] --> B[[RNA preparation]] B --> C[[Library Generation]] C --> D[[Sequencing]] D --> E[[QC of Raw Data]] E --> F[[Read Alignment]] F --> G[[Quantification]] G --> H[[Differential Expression Analysis]] H --> I[[Functional Profiling]] style B fill:#228B22,stroke:#333,stroke-width:2px,color:#ffffff,font-weight:bold
flowchart TD A[[Hypothesis & Experiment Design]] --> B[[RNA preparation]] B --> C[[Library Generation]] C --> D[[Sequencing]] D --> E[[QC of Raw Data]] E --> F[[Read Alignment]] F --> G[[Quantification]] G --> H[[Differential Expression Analysis]] H --> I[[Functional Profiling]] style C fill:#228B22,stroke:#333,stroke-width:2px,color:#ffffff,font-weight:bold
Bioanalyzer, TapeStation, Qubitflowchart TD A[[Hypothesis & Experiment Design]] --> B[[RNA preparation]] B --> C[[Library Generation]] C --> D[[Sequencing]] D --> E[[QC of Raw Data]] E --> F[[Read Alignment]] F --> G[[Quantification]] G --> H[[Differential Expression Analysis]] H --> I[[Functional Profiling]] style D fill:#228B22,stroke:#333,stroke-width:2px,color:#ffffff,font-weight:bold
flowchart TD A[[Hypothesis & Experiment Design]] --> B[[RNA preparation]] B --> C[[Library Generation]] C --> D[[Sequencing]] D --> E[[QC of Raw Data]] E --> F[[Read Alignment]] F --> G[[Quantification]] G --> H[[Differential Expression Analysis]] H --> I[[Functional Profiling]] style E fill:#228B22,stroke:#333,stroke-width:2px,color:#ffffff,font-weight:bold
FastQC, MultiQC
Learn more about Good Illumina Data and Bad Illumina Data
flowchart TD A[[Hypothesis & Experiment Design]] --> B[[RNA preparation]] B --> C[[Library Generation]] C --> D[[Sequencing]] D --> E[[QC of Raw Data]] E --> F[[Read Alignment]] F --> G[[Quantification]] G --> H[[Differential Expression Analysis]] H --> I[[Functional Profiling]] style F fill:#228B22,stroke:#333,stroke-width:2px,color:#ffffff,font-weight:bold
HISAT2, STAR, Salmon, Kallisto, RSeQC, MultiQCflowchart TD A[[Hypothesis & Experiment Design]] --> B[[RNA preparation]] B --> C[[Library Generation]] C --> D[[Sequencing]] D --> E[[QC of Raw Data]] E --> F[[Read Alignment]] F --> G[[Quantification]] G --> H[[Differential Expression Analysis]] H --> I[[Functional Profiling]] style G fill:#228B22,stroke:#333,stroke-width:2px,color:#ffffff,font-weight:bold
Annotation
Quantification
Tools: Salmon, Kallisto, featureCounts, RSeQC, MultiQC
Source : nf-core rnaseq: Output
flowchart TD A[[Hypothesis & Experiment Design]] --> B[[RNA preparation]] B --> C[[Library Generation]] C --> D[[Sequencing]] D --> E[[QC of Raw Data]] E --> F[[Read Alignment]] F --> G[[Quantification]] G --> H[[Differential Expression Analysis]] H --> I[[Functional Profiling]] style H fill:#228B22,stroke:#333,stroke-width:2px,color:#ffffff,font-weight:bold
DESeq2, edgeR, limma-voomflowchart TD A[[Hypothesis & Experiment Design]] --> B[[RNA preparation]] B --> C[[Library Generation]] C --> D[[Sequencing]] D --> E[[QC of Raw Data]] E --> F[[Read Alignment]] F --> G[[Quantification]] G --> H[[Differential Expression Analysis]] H --> I[[Functional Profiling]] style I fill:#228B22,stroke:#333,stroke-width:2px,color:#ffffff,font-weight:bold
clusterProfiler, gProfiler, DAVIDflowchart TD A[[Hypothesis & Experiment Design]] --> B[[RNA preparation]] B --> C[[Library Generation]] C --> D[[Sequencing]] D --> E[[QC of Raw Data]] E --> F[[Read Alignment]] F --> G[[Quantification]] G --> H[[Differential Expression Analysis]] H --> I[[Functional Profiling]] %% style H fill:#228B22,stroke:#333,stroke-width:2px,color:#ffffff,font-weight:bold %% style I fill:#228B22,stroke:#333,stroke-width:2px,color:#ffffff,font-weight:bold
RNA-Seq_ProjectName/
├── data/
│ ├── raw_data/
│ ├── reference_data/
│ ├── meta_data/
│ └── processed_data/
│ ├── trimmed_data/
│ ├── alignments_data/
│ └── counts_data/
│
├── results/
│ ├── qc/
│ ├── differential_expression/
│ ├── functional_profiling/
│ └── final_figures/
│
├── reports/
├── scripts/
├── R/
├── logs/
└── README.mdraw_data/ : Sequencing data files (FASTQ format)
reference_data/ : Reference genome
reference_data/ : annotation files
alignments_data/ : Aligned reads files (BAM/SAM format)
counts_data/ : Gene expression counts matrix
Source : 1. NGS Analysis 2. hbctraining